Supplemental Methods

1 Tributary detection efficiency

Detection efficiency at the in-stream PIT tag array closest to the mouth of the tributary (the confluence of the tributary with the mainstem Columbia or Snake River) was estimated for each tributary state. However, detection efficiency was not modeled for three tributaries of the Snake River (the Salmon River, the Grande Ronde River, and the Clearwater River), as these tributaries did not have a detection site on the mainstem of the tributary within 100 km of the confluence. The data used to estimate detection efficiency at the river mouth sites was detections at the river mouth site and detections anywhere upstream of the river mouth site. In this analysis, we only included fish that were detected at a site upstream of the river mouth site, and then used a binary indicator to record if those fish were also detected at the river mouth site.

We modeled detection efficiency in tributaries using logistic regression based on two predictors: 1) changes in antenna configurations over time, and 2) the discharge in the tributary. Changes in antenna configurations were identified from the operational history of the site, based on antennas being installed, decommissioned, upgraded, or moved. Changes in antenna configurations are identified in Table S1. Discharge was included as a predictor based on our hypothesis that river stage would influence the antenna coverage of the river channel. Discharge data were queried from USGS by finding the station on the interactive USGS dashboard closest the river mouth array and navigating to the data page for the specific site. Discharge data were available for all tributaries except Fifteenmile Creek and the Imnaha River; detection efficiency in these tributaries was therefore only modeled as a function of antenna configurations. We processed discharge data for inclusion in the model by taking the mean discharge across the run year.

Table S1: Tributary PIT tag antenna configurations used in detection efficiency estimation. Years refer to the Steelhead run years in which the site was active in a specific configuration. Site refers to the PIT tag detection site chosen for the detection efficiency estimation, based on its proximity to the mouth of the tributary. Configuration refers to the configuration of antennas at the site, where Initial is the name given to the antenna configuration at the site at the start of the time series, and any subsequent changes from the initial configuration at the site are noted in this column.

Tributary Years Site Configuration
Hood River 12/13-23/24 Hood River Mouth (HRM) Initial
Fifteenmile Creek 11/12-18/19 Fifteenmile Ck at Eighmile Ck (158) Initial
Deschutes River 13/14-18/19 Deschutes River Mouth (DRM) Initial
John Day River 12/13-23/24 John Day River, McDonald Ferry (JD1) Initial
Umatilla River 06/07-13/14 Three Mile Falls Dam (TMF) Initial
Umatilla River 14/15-23/24 Three Mile Falls Dam (TMF) Antenna installation at entrance to adult ladder
Walla Walla River 05/06-11/12 Oasis Road Bridge (ORB) Initial
Walla Walla River 12/13-14/15 Oasis Road Bridge (ORB) and Walla Walla R at Pierce RV Pk (PRV) Initial configuration where two mouth sites were operational simultaneously and their joint detection efficiency was estimated
Walla Walla River 15/16-18/19 Walla Walla R at Pierce RV Pk (PRV) Initial
Walla Walla River 19/20-23/24 Walla Walla River Barge Array (WWB) Initial
Yakima River 05/06-23/24 Prosser Diversion Dam (PRO) Initial
Wenatchee River 10/11-23/24 Lower Wenatchee River (LWE) Initial
Entiat River 07/08-23/24 Lower Entiat River (ENL) Initial
Methow River 09/10-16/17 Lower Methow River at Pateros (LMR) Initial
Methow River 17/18-23/24 Lower Methow River at Pateros (LMR) Site was moved 5 km upstream and transceivers replaced
Okanogan River 13/14-23/24 Lower Okanogan Instream Array (OKL) Initial
Tucannon River 10/11-19/20 Lower Tucannon River (LTR) Initial
Tucannon River 20/21-23/24 Lower Tucannon River (LTR) All antennas replaced, additional antenna installed
Asotin Creek 11/12-17/18 Asotin Creek Mouth (ACM) Initial
Asotin Creek 18/19-23/24 Asotin Creek Mouth (ACM) All components replaced and upgraded
Imnaha River 10/11-23/24 Lower Imnaha River ISA @ km 7 (IR1) Initial

For our model of detection efficiency, the data included all fish that were detected at a site upstream of the river mouth. We then denote \(z_i\) as the detection of fish \(i\) at the river mouth site, \(p_{det,i}\) as the probability of detection for fish \(i\), \(\alpha_{j,k}\) as the antenna configuration for tributary \(j\) under configuration \(k\), \(\beta_j\) as the slope for the effect of discharge, and \(x_{j,t}\) as the mean discharge for tributary \(j\) in run year \(t\). The model for detection efficiency was as follows:

\[ z_i \sim Bernoulli(p_{det,i}) \\ logit(p_{det,i}) =\alpha_{j,k} + \beta_j x_{j,t} \]

The above model was implemented in Stan (Carpenter et al., 2017), with 3 chains run for 5,000 warmup and 5,000 sampling iterations each. Discharge values were Z-scored prior to the model being fit. The posteriors from this model for each of the \(\alpha\) (site configuration intercepts) and \(\beta\) (effect of discharge) terms were used as priors in the primary Stan model that was used to estimate movement. The resulting detection efficiency correction for each run year can be found in Supplemental Results 4.

2 Covariate data processing

Temperature data

Due to the noise and gaps inherent to the temperature data, a series of steps were performed to clean this data. First, plots of temperature were manually inspected and sequential runs of temperature points that were outside of the range of possible values for that time of year were removed. Next, a filtering algorithm was applied to remove any temperature values that were more than four degrees outside of the interannual average temperature value for that day of the year, as well as any values that were more than two degrees outside of the 7-day moving average. To address the incomplete temporal resolution for temperature at each dam in our modeling framework, a state-space model was fit using the MARSS package (Holmes et al. 2012). The inputs for this model were the cleaned temperature data at the forebay and tailrace for the eight dams (a total of 16 temperature time series). The model was structured with only a single process (the basin-scale temperature) and 16 observations of that process. Each dam had a different offset/bias term (8 total). Model-estimated temperatures on each day for each dam were then exported by using the estimate of the basin-scale temperature plus the dam-specific offset.

To estimate the temperatures experienced by fish, the median residence time in each state in our model was first calculated. To do so, we calculated the difference between the date on which a fish was observed exiting a state and the date on which a fish was observed entering a state, and then computed the state-specific median across all fish. However, for the two furthest upstream states (upstream of Lower Granite Dam and upstream of Wells Dam), above which there are no more dams with fish passage, residence times were significantly longer and were found to be bimodal. These furthest upstream states are also observed to have more variability in median residence times because of their position in the PIT tag array network (see plots below). Based on our hypothesis that movement decisions are made soon after a fish enters a state, we fit a two-component mixture model using the mixtools package in R (Benaglia et al. 2010) to residence times in these states and used the median residence time for fish in the first mode. The mean temperature experienced by each fish while in a state was estimated as the mean temperature across a window of time defined as the date the fish was observed entering a state plus the median residence time for all fish in that state.

Spill data

Daily average spill (in thousands of cubic feet per second) was queried from the Columbia Basin Conditions portal from the DART page for the eight dams that were modeled as the boundaries of states (Bonneville, McNary, Priest Rapids, Rock Island, Rocky Reach, Wells, Ice Harbor, and Lower Granite). Spill data were processed in two different ways to facilitate the inclusion of two hypothesized relationships between spill and fish fallback over dams. For en-route fallback, spill volume was processed in the same way as temperature: by taking the mean volume of spill across the residence time window. For post-overshoot fallback, spill volume was converted into days of winter spill, by counting the number of days that had nonzero spill in the months of January, February, and March for each year.

Residence time visualization

Residence time was calculated across all fish and all years. Variability in residence time by year (visualized below as the median residence time by year with the error bars showing the 95% interquantile range) was generally not significant. Furthermore, dividing up the dataset by year would have led to small sample sizes in some years, leading to an unrepresentative residence time.

Residence time for fish in the state between Bonneville and McNary Dams.

Residence time for fish in the state between Bonneville and McNary Dams.

Residence time for fish in the state between McNary and Ice Harbor/Priest Rapids Dams.

Residence time for fish in the state between McNary and Ice Harbor/Priest Rapids Dams.

Residence time for fish in the state between Priest Rapids and Rock Island Dams.

Residence time for fish in the state between Priest Rapids and Rock Island Dams.

Residence time for fish in the state between Rock Island and Rocky Reach Dams.

Residence time for fish in the state between Rock Island and Rocky Reach Dams.

Residence time for fish in the state between Rocky Reach and Wells Dams.

Residence time for fish in the state between Rocky Reach and Wells Dams.

Residence time for fish in the state between Ice Harbor and Lower Granite Dams.

Residence time for fish in the state between Ice Harbor and Lower Granite Dams.

Residence time for fish in the state upstream of Wells Dam.

Residence time for fish in the state upstream of Wells Dam.

Residence time for fish in the state upstream of Lower Granite Dam.

Residence time for fish in the state upstream of Lower Granite Dam.

Supplemental Results

1 Sample sizes

The number of fish per run year from each combination of natal tributary, rearing type (natural or hatchery origin), and juvenile pathway (transported or in-river migrants).
Population 05/06 06/07 07/08 08/09 09/10 10/11 11/12 12/13 13/14 14/15 15/16 16/17 17/18 18/19 19/20 20/21 21/22 22/23 23/24 Total
Fifteenmile Creek (N, in-river) 0 0 0 11 47 89 95 33 32 37 24 10 18 43 39 6 1 0 5 490
Deschutes River (N, in-river) 0 0 38 68 117 113 109 81 180 97 49 40 28 39 45 27 0 3 0 1034
John Day River (N, in-river) 68 119 114 247 347 279 287 151 261 243 217 88 80 67 113 72 50 68 113 2984
Umatilla River (H, in-river) 9 12 59 80 115 77 64 24 13 36 42 29 16 1 1 6 7 36 86 713
Umatilla River (N, in-river) 2 10 17 21 14 13 81 65 68 171 278 145 117 62 58 34 53 113 88 1410
Walla Walla River (H, in-river) 33 32 25 301 415 222 261 120 111 163 114 112 119 97 58 41 48 111 65 2448
Walla Walla River (N, in-river) 11 11 10 8 61 95 115 90 57 75 72 19 27 19 23 15 23 39 27 797
Yakima River (N, in-river) 15 12 18 16 33 23 40 18 45 78 93 38 42 46 60 50 44 40 66 777
Wenatchee River (H, in-river) 399 400 350 450 818 523 427 380 183 189 173 25 38 27 20 69 3 31 28 4533
Wenatchee River (N, in-river) 0 0 2 8 71 73 53 32 31 39 44 9 7 3 15 14 8 7 6 422
Entiat River (N, in-river) 0 3 8 7 75 74 55 26 43 66 56 34 8 15 17 12 4 5 5 513
Methow River (H, in-river) 1866 3088 478 35 128 58 319 324 292 286 289 108 126 50 31 86 92 113 139 7908
Methow River (N, in-river) 0 0 6 13 42 24 33 18 43 44 51 22 13 7 25 17 19 20 17 414
Okanogan River (H, in-river) 172 36 8 17 9 9 117 134 100 141 115 56 78 42 18 50 20 39 76 1237
Tucannon River (H, in-river) 56 40 382 322 576 231 162 78 96 112 95 57 46 38 22 14 39 95 82 2543
Tucannon River (H, transported) 2 43 167 101 63 28 4 5 25 29 38 19 23 13 13 6 3 5 7 594
Tucannon River (N, in-river) 33 14 22 8 50 43 50 54 45 59 58 9 22 9 20 20 13 25 26 580
Tucannon River (N, transported) 2 10 18 7 0 1 0 1 0 0 1 0 3 4 2 10 1 2 1 63
Clearwater River (H, in-river) 13 30 46 163 75 469 592 492 241 322 266 467 155 234 70 208 128 508 365 4844
Clearwater River (H, transported) 23 4 2 13 20 210 129 158 74 46 51 104 5 21 3 109 41 44 29 1086
Clearwater River (N, in-river) 13 6 20 51 87 128 105 63 69 234 84 32 20 15 22 44 16 43 23 1075
Clearwater River (N, transported) 24 23 30 28 51 72 35 48 19 51 93 50 7 8 23 67 8 10 10 657
Asotin Creek (N, transported) 0 1 11 19 19 18 23 27 18 43 37 13 4 9 7 10 8 7 1 275
Asotin Creek (N, in-river) 0 0 1 4 11 9 19 18 61 64 20 15 14 6 10 22 11 30 17 332
Grande Ronde River (H, in-river) 18 10 61 75 680 387 469 290 309 427 401 281 305 187 93 99 118 206 240 4656
Grande Ronde River (H, transported) 1 92 102 74 455 232 185 124 73 144 148 86 40 38 54 82 28 32 39 2029
Grande Ronde River (N, in-river) 8 2 19 21 50 70 65 49 54 53 47 19 13 9 19 10 6 15 8 537
Grande Ronde River (N, transported) 27 13 16 16 15 13 21 15 9 9 21 17 6 10 9 14 3 0 5 239
Salmon River (H, in-river) 14 18 63 71 1003 740 1017 586 699 753 433 262 208 149 116 143 162 192 241 6870
Salmon River (H, transported) 22 2 4 7 647 493 454 363 266 384 277 165 88 68 68 154 57 37 49 3605
Salmon River (N, in-river) 10 4 8 36 117 80 87 45 99 135 62 25 16 17 20 23 21 41 27 873
Salmon River (N, transported) 7 17 11 13 41 24 39 25 17 13 28 7 2 4 11 25 6 9 14 313
Imnaha River (H, in-river) 25 31 28 31 356 233 262 91 242 242 225 84 114 68 49 54 108 168 163 2574
Imnaha River (H, transported) 6 5 5 2 378 209 130 70 95 166 182 72 50 35 24 41 13 13 29 1525
Imnaha River (N, in-river) 19 5 11 45 96 77 79 42 63 79 84 34 21 16 21 30 31 42 52 847
Imnaha River (N, transported) 19 9 24 79 55 47 64 28 30 50 78 24 16 8 19 23 11 5 15 604
Total 2917 4102 2184 2468 7137 5486 6047 4168 4063 5080 4346 2577 1895 1484 1218 1707 1204 2154 2164 62401

2 Covariate data summaries

In this section, we present summaries of the three basin condition covariates incorporated in this model: temperature, spill volume, and number of winter spill days. We first present summary tables that show the differences in these covariates by run year and by dam, and then present figures that show the fine-scale details in these trends by dam and across year.

Mean temperature (degrees Celsius) by run year across the dams in this study. Dam abbreviations are the ones listed in Table 1 of the main text.
Run Year BON MCN PRA RIS RRE WEL ICH LGR
05/06 12.60 11.81 10.93 10.55 10.54 10.36 11.90 11.01
06/07 12.70 11.91 11.03 10.66 10.64 10.46 12.00 11.11
07/08 12.34 11.55 10.67 10.29 10.28 10.10 11.64 10.75
08/09 12.14 11.35 10.47 10.10 10.09 9.90 11.44 10.55
09/10 12.80 12.01 11.13 10.75 10.74 10.56 12.10 11.21
10/11 12.36 11.58 10.70 10.32 10.31 10.13 11.67 10.78
11/12 12.18 11.39 10.52 10.14 10.13 9.94 11.49 10.59
12/13 12.81 12.02 11.14 10.77 10.75 10.57 12.11 11.22
13/14 12.92 12.13 11.26 10.88 10.87 10.68 12.23 11.33
14/15 13.72 12.93 12.06 11.68 11.67 11.49 13.03 12.13
15/16 14.02 13.23 12.35 11.98 11.96 11.78 13.32 12.43
16/17 13.08 12.30 11.42 11.04 11.03 10.85 12.39 11.50
17/18 13.29 12.50 11.62 11.25 11.23 11.05 12.59 11.70
18/19 13.24 12.45 11.57 11.19 11.18 11.00 12.54 11.65
19/20 13.25 12.46 11.59 11.21 11.20 11.01 12.56 11.66
20/21 13.15 12.36 11.49 11.11 11.10 10.91 12.46 11.56
21/22 13.18 12.39 11.52 11.14 11.13 10.94 12.49 11.59
22/23 12.88 12.09 11.21 10.83 10.82 10.64 12.18 11.29
23/24 13.90 13.11 12.23 11.86 11.85 11.66 13.20 12.31
Mean spill volume (kcfs) by run year across the dams in this study. Dam abbreviations are the ones listed in Table 1 of the main text.
Run Year BON MCN PRA RIS RRE WEL ICH LGR
05/06 41.81 48.98 22.65 9.17 5.45 6.93 16.50 12.10
06/07 41.00 44.03 13.77 8.11 5.14 9.49 13.98 8.91
07/08 42.10 37.95 8.24 8.01 3.82 4.60 13.54 9.87
08/09 43.57 45.81 10.91 7.92 4.99 6.90 20.56 12.31
09/10 36.58 32.68 8.55 5.91 2.01 2.86 14.49 8.67
10/11 51.84 65.60 22.67 11.34 7.73 8.77 22.48 14.32
11/12 65.71 82.03 43.37 18.61 18.67 21.32 27.35 15.30
12/13 47.16 64.59 41.49 16.55 18.44 17.36 16.08 9.08
13/14 43.32 51.86 21.70 15.52 6.61 7.12 15.22 8.78
14/15 42.42 46.22 19.42 13.09 5.14 4.86 13.89 7.98
15/16 39.32 35.75 14.26 7.67 3.48 4.63 12.97 6.92
16/17 71.28 74.21 35.89 20.11 19.61 12.14 29.43 19.21
17/18 59.17 69.46 35.61 24.07 18.67 17.40 27.93 14.83
18/19 42.83 49.98 14.60 8.49 5.45 6.87 23.44 12.87
19/20 43.00 49.63 13.27 9.74 6.19 5.36 16.00 13.87
20/21 43.06 49.52 19.19 14.76 10.09 10.14 14.71 13.45
21/22 42.98 47.77 15.57 9.05 3.11 6.65 12.65 10.96
22/23 51.71 65.12 30.36 20.68 11.20 14.26 21.91 16.43
23/24 43.82 38.14 10.31 5.97 1.58 2.68 16.60 17.13
Number of winter (January - March) spill days by run year across the dams in this study. Dam abbreviations are the ones listed in Table 1 of the main text. Please note that Bonneville Dam is not included in this plot because it is not an overshoot dam for any populations in our study.
Run Year MCN PRA RIS RRE WEL ICH LGR
05/06 7 3 0 2 9 13 0
06/07 20 10 2 15 25 8 7
07/08 2 6 0 4 9 1 2
08/09 1 14 1 17 13 2 1
09/10 0 0 1 5 1 2 4
10/11 71 29 27 19 21 17 3
11/12 20 11 6 17 14 15 9
12/13 17 17 4 18 18 10 1
13/14 27 27 29 31 23 16 9
14/15 74 52 6 42 36 6 2
15/16 11 6 36 8 3 6 2
16/17 49 43 23 49 19 48 36
17/18 33 41 52 29 65 59 8
18/19 0 8 5 13 20 15 2
19/20 29 20 33 50 10 4 2
20/21 21 35 41 39 24 14 14
21/22 59 46 34 10 42 15 13
22/23 14 28 12 6 13 14 25
23/24 31 25 20 10 6 31 52

In the panels below, plots of temperature, spill volume, and number of winter spill days are shown for each of the mainstem dams in this study. Please note that because the temperature visualized here (and incorporated into the model) is an output from a MARSS model that estimated a single temperature state for the entire Columbia River Basin, all dams have the same trends in temperature, but with different overall magnitudes. The choice to model the entire basin as a single temperature trend was necessitated by significant gaps in data at some dams.

Bonneville Dam

McNary Dam

Priest Rapids Dam

Rock Island Dam

Rocky Reach Dam

Wells Dam

Ice Harbor Dam

Lower Granite Dam

3 Post-overshoot fallback timing

Because PIT-tag arrays are largely incapable of directly detecting fallback (most dams do not have PIT antennas in the spillway), we were not able to observe post-overshoot fallback directly. As such, we sought to characterize spillway passage availability during the time of potential fallback as informed by subsequent detections. The figure below shows the next detection after a post-overshoot fallback movement, showing the overall pattern of post-overshoot fallback timing.

Timing of detections directly following a post-overshoot fallback movement.

Timing of detections directly following a post-overshoot fallback movement.

The table below shows the proportion of fish from each population that received the January-March spill days covariate, based on their fallback timing.

Proportion of overshoot state visits that received the January-March spill days covariate. In Window refers to the number of fish that may have fallen back during the window of time between January 1 and March 31, and therefore received the January-March spill days covariate. Total is the total number of fish that overshot, and proportion is the proportion of the total fish that may have fallen back in the January-March window.
population In Window total proportion
Deschutes River natural in-river 6 11 0.55
John Day River natural in-river 1328 2703 0.49
Fifteenmile Creek natural in-river 31 55 0.56
Umatilla River natural in-river 482 951 0.51
Umatilla River hatchery in-river 236 366 0.64
Yakima River natural in-river 71 215 0.33
Walla Walla River natural in-river 272 464 0.59
Walla Walla River hatchery in-river 1335 2478 0.54
Entiat River natural in-river 134 197 0.68
Wenatchee River natural in-river 19 73 0.26
Wenatchee River hatchery in-river 1820 4042 0.45
Tucannon River natural in-river 288 373 0.77
Tucannon River natural transported 14 17 0.82
Tucannon River hatchery in-river 1236 1601 0.77
Tucannon River hatchery transported 95 114 0.83

To expand on the data presented in the previous table, the figures below show the timing of observations of overshoot (first point) and first observation following post-overshoot fallback (second point) for each fish from a given population. Red points indicate terminal overshoot observations (where fish were not seen again below an overshoot dam following overshoot). Lines connecting overshoot observations with observations following post-overshoot fallback indicate the time period in which a fallback event must have occurred. Dashed green lines indicate the winter months (January, February, and March) that were used to characterize the likely spill conditions encountered by fish in overshoot states. In our model, any fish that was last observed overshooting (red dots) or where based on their detection history, may have fallen back during January, February, or March (any black lines that are at least partially between the two dashed green lines) are affected by the winter spill days covariate.

Deschutes (N)

John Day (N)

Fifteenmile (N)

Umatilla (N)

Umatilla (H)

Yakima (N)

Walla Walla (N)

Walla Walla (H)

Entiat (N)

Wenatchee (N)

Wenatchee (H)

Tucannon (N, in-river)

Tucannon (N, transported)

Tucannon (H, in-river)

Tucannon (H, transported)

4 Detection efficiency estimation

The figures below show the estimated relationship between discharge and detection efficiency at the river mouth sites for different tributaries in different site configurations. As mentioned in Supplemental Methods 1, our a priori hypothesis was that detection efficiency would generally decrease as discharge increases, as increased flow would increase the area that is outside the detection range of the PIT tag arrays. However, as seen below, for some tributaries we estimated a positive relationship between discharge and detection efficiency. This estimated relationship may be the result of spurious correlations, or may be a true positive relationship. Spurious correlations may be due to changes to the PIT-tag antenna configurations or operations that were not captured in our site configuration covariate in the detection level efficiency estimation. While we attempted to capture major changes, an inspection of the operational history and event log summary at each site on the PTAGIS Interrogation Site Metadata reveals numerous events (e.g., battery failures, flood damage, equipment failures and repairs) that may have affected the detection efficiency and confounded the relationship with discharge. However, there may have also been a true positive relationship between discharge and detections efficiency, as there are reasons that higher discharge may actually be favorable for detection efficiency. For example, PIT tag arrays are known to perform poorly in cases where two or more fish pass over the antenna at the same time (Greenberg and Ciller 2000), which may be more likely when flows are low. Furthermore, fish behavior can change with changing stream conditions, and the ability of PIT tag interrogation systems to detect fish can change with conditions that are affected by flow, including water temperature, conductivity, and air temperature (Connolly et al. 2008).

Fifteenmile Creek

Fifteenmile Creek, estimated detection efficiency.
Fifteenmile Creek, estimated detection efficiency.

Deschutes River

Deschutes River, estimated detection efficiency.
Deschutes River, estimated detection efficiency.

John Day River

John Day River, estimated detection efficiency.
John Day River, estimated detection efficiency.

Umatilla River

Umatilla River, estimated detection efficiency in time period 1.
Umatilla River, estimated detection efficiency in time period 1.
Umatilla River, estimated detection efficiency in time period 2.
Umatilla River, estimated detection efficiency in time period 2.

Walla Walla River

Walla Walla River, estimated detection efficiency in time period 1.
Walla Walla River, estimated detection efficiency in time period 1.
Walla Walla River, estimated detection efficiency in time period 2.
Walla Walla River, estimated detection efficiency in time period 2.
Walla Walla River, estimated detection efficiency in time period 3.
Walla Walla River, estimated detection efficiency in time period 3.
Walla Walla River, estimated detection efficiency in time period 4.
Walla Walla River, estimated detection efficiency in time period 4.

Yakima River

Yakima River, estimated detection efficiency.
Yakima River, estimated detection efficiency.

Wenatchee River

Wenatchee River, estimated detection efficiency.
Wenatchee River, estimated detection efficiency.

Entiat River

Entiat River, estimated detection efficiency.
Entiat River, estimated detection efficiency.

Methow River

Methow River, estimated detection efficiency in time period 1.
Methow River, estimated detection efficiency in time period 1.
Methow River, estimated detection efficiency in time period 2.
Methow River, estimated detection efficiency in time period 2.

Okanogan River

Okanogan River, estimated detection efficiency.
Okanogan River, estimated detection efficiency.

Tucannon River

Tucannon River, estimated detection efficiency in time period 1.
Tucannon River, estimated detection efficiency in time period 1.
Tucannon River, estimated detection efficiency in time period 2.
Tucannon River, estimated detection efficiency in time period 2.

Asotin Creek

Asotin Creek, estimated detection efficiency in time period 1.
Asotin Creek, estimated detection efficiency in time period 1.
Asotin Creek, estimated detection efficiency in time period 2.
Asotin Creek, estimated detection efficiency in time period 2.

Imnaha River

Imnaha River, estimated detection efficiency.
Imnaha River, estimated detection efficiency.

5 Model diagnostic figures

The R-hat convergence diagnostic for each of the six models run. The R-hat convergence diagnostic compares the between- and within-chain estimates for model parameters and other univariate quantities of interest. If chains have not mixed well (i.e., the between- and within-chain estimates don’t agree), R-hat is larger than 1. R-hat values should be less than 1.05, and all parameters here have an R-hat of less than 1.01.
The R-hat convergence diagnostic for each of the six models run. The R-hat convergence diagnostic compares the between- and within-chain estimates for model parameters and other univariate quantities of interest. If chains have not mixed well (i.e., the between- and within-chain estimates don’t agree), R-hat is larger than 1. R-hat values should be less than 1.05, and all parameters here have an R-hat of less than 1.01.


Bulk Effective Sample Size (bulk-ESS) using rank normalized draws, for each of the six models run. Bulk-ESS is useful measure for sampling efficiency in the bulk of the distribution (related to efficiency of mean and median estimates), and is well defined even if the chains do not have finite mean or variance. Both bulk-ESS and tail-ESS should be at least 100 (approximately) per Markov Chain in order to be reliable and indicate that estimates of respective posterior quantiles are reliable.
Bulk Effective Sample Size (bulk-ESS) using rank normalized draws, for each of the six models run. Bulk-ESS is useful measure for sampling efficiency in the bulk of the distribution (related to efficiency of mean and median estimates), and is well defined even if the chains do not have finite mean or variance. Both bulk-ESS and tail-ESS should be at least 100 (approximately) per Markov Chain in order to be reliable and indicate that estimates of respective posterior quantiles are reliable.


Tail Effective Sample Size (tail-ESS) using rank normalized draws, for each of the six models run. Tail-ESS is produces by computing the minimum of effective sample sizes for 5% and 95% quantiles. Tail-ESS is useful measure for sampling efficiency in the tails of the distribution (related to efficiency of variance and tail quantile estimates). Both bulk-ESS and tail-ESS should be at least 100 (approximately) per Markov Chain in order to be reliable and indicate that estimates of respective posterior quantiles are reliable.
Tail Effective Sample Size (tail-ESS) using rank normalized draws, for each of the six models run. Tail-ESS is produces by computing the minimum of effective sample sizes for 5% and 95% quantiles. Tail-ESS is useful measure for sampling efficiency in the tails of the distribution (related to efficiency of variance and tail quantile estimates). Both bulk-ESS and tail-ESS should be at least 100 (approximately) per Markov Chain in order to be reliable and indicate that estimates of respective posterior quantiles are reliable.

6 Covariate correlations

All dams

Correlation between spill and flow across all run years in the dataset, by dam.
Dam Mean Flow Mean Spill R-squared
Bonneville Dam 177.04 46.73 0.61
McNary Dam 168.59 52.07 0.80
Priest Rapids Dam 117.07 20.84 0.72
Rock Island Dam 113.00 12.22 0.60
Rocky Reach Dam 109.27 8.12 0.61
Wells Dam 109.43 8.80 0.65
Ice Harbor Dam 45.87 18.17 0.82
Lower Granite Dam 45.33 12.23 0.71
Correlation between spill and temperature across all run years in the dataset, by dam.
Dam Mean temp Mean Spill R-squared
Bonneville Dam 13.11 46.73 0.08
McNary Dam 12.32 52.07 0.04
Priest Rapids Dam 11.45 20.84 0.03
Rock Island Dam 11.07 12.22 0.04
Rocky Reach Dam 11.06 8.12 0.01
Wells Dam 10.87 8.80 0.01
Ice Harbor Dam 12.42 18.17 0.00
Lower Granite Dam 11.52 12.23 0.02

Bonneville Dam

Correlation between spill and flow for each year, for Bonneville Dam
Run Year Mean Flow Mean Spill R-squared
05/06 180.17 41.81 0.53
06/07 181.43 41.00 0.50
07/08 158.63 42.10 0.63
08/09 176.30 43.57 0.72
09/10 140.96 36.58 0.61
10/11 202.42 51.84 0.63
11/12 226.12 65.71 0.89
12/13 200.28 47.16 0.80
13/14 179.49 43.32 0.62
14/15 179.59 42.42 0.17
15/16 165.34 39.32 0.23
16/17 213.67 71.28 0.74
17/18 211.81 59.17 0.70
18/19 167.99 42.83 0.63
19/20 157.30 43.00 0.46
20/21 169.73 43.06 0.55
21/22 162.99 42.98 0.27
22/23 180.03 51.71 0.86
23/24 137.09 43.82 0.64
Correlation between spill and temperature for each year, for Bonneville Dam
Run Year Mean Temperature Mean Spill R-squared
05/06 12.60 41.81 0.15
06/07 12.70 41.00 0.18
07/08 12.34 42.10 0.16
08/09 12.14 43.57 0.13
09/10 12.80 36.58 0.19
10/11 12.36 51.84 0.05
11/12 12.18 65.71 0.07
12/13 12.81 47.16 0.14
13/14 12.92 43.32 0.12
14/15 13.72 42.42 0.13
15/16 14.02 39.32 0.21
16/17 13.08 71.28 0.00
17/18 13.29 59.17 0.06
18/19 13.24 42.83 0.14
19/20 13.25 43.00 0.14
20/21 13.15 43.06 0.09
21/22 13.18 42.98 0.08
22/23 12.88 51.71 0.05
23/24 13.90 43.82 0.08

McNary Dam

Correlation between spill and flow for each year, for McNary Dam
Run Year Mean Flow Mean Spill R-squared
05/06 171.49 48.98 0.70
06/07 170.81 44.03 0.74
07/08 149.40 37.95 0.81
08/09 164.91 45.81 0.86
09/10 132.37 32.68 0.82
10/11 190.75 65.60 0.87
11/12 215.33 82.03 0.97
12/13 192.16 64.59 0.92
13/14 171.66 51.86 0.86
14/15 174.30 46.22 0.61
15/16 156.69 35.75 0.55
16/17 204.29 74.21 0.85
17/18 204.60 69.46 0.82
18/19 159.08 49.98 0.86
19/20 150.22 49.63 0.78
20/21 162.52 49.52 0.81
21/22 155.80 47.77 0.55
22/23 173.80 65.12 0.91
23/24 129.43 38.14 0.74
Correlation between spill and temperature for each year, for McNary Dam
Run Year Mean Temperature Mean Spill R-squared
05/06 11.81 48.98 0.11
06/07 11.91 44.03 0.14
07/08 11.55 37.95 0.15
08/09 11.35 45.81 0.10
09/10 12.01 32.68 0.18
10/11 11.58 65.60 0.00
11/12 11.39 82.03 0.05
12/13 12.02 64.59 0.14
13/14 12.13 51.86 0.06
14/15 12.93 46.22 0.06
15/16 13.23 35.75 0.13
16/17 12.30 74.21 0.00
17/18 12.50 69.46 0.02
18/19 12.45 49.98 0.06
19/20 12.46 49.63 0.07
20/21 12.36 49.52 0.08
21/22 12.39 47.77 0.02
22/23 12.09 65.12 0.04
23/24 13.11 38.14 0.07

Priest Rapids Dam

Correlation between spill and flow for each year, for Priest Rapids Dam
Run Year Mean Flow Mean Spill R-squared
05/06 114.99 22.65 0.41
06/07 122.40 13.77 0.51
07/08 106.20 8.24 0.58
08/09 106.28 10.91 0.69
09/10 88.09 8.55 0.50
10/11 125.87 22.67 0.68
11/12 147.35 43.37 0.93
12/13 147.75 41.49 0.86
13/14 123.81 21.70 0.78
14/15 126.11 19.42 0.52
15/16 111.21 14.26 0.49
16/17 138.56 35.89 0.85
17/18 138.43 35.61 0.85
18/19 104.91 14.60 0.75
19/20 101.01 13.27 0.58
20/21 117.17 19.19 0.74
21/22 115.20 15.57 0.34
22/23 120.31 30.36 0.89
23/24 84.08 10.31 0.36
Correlation between spill and temperature for each year, for Priest Rapids Dam
Run Year Mean Temperature Mean Spill R-squared
05/06 10.93 22.65 0.15
06/07 11.03 13.77 0.03
07/08 10.67 8.24 0.14
08/09 10.47 10.91 0.09
09/10 11.13 8.55 0.16
10/11 10.70 22.67 0.02
11/12 10.52 43.37 0.04
12/13 11.14 41.49 0.14
13/14 11.26 21.70 0.06
14/15 12.06 19.42 0.00
15/16 12.35 14.26 0.04
16/17 11.42 35.89 0.01
17/18 11.62 35.61 0.01
18/19 11.57 14.60 0.06
19/20 11.59 13.27 0.08
20/21 11.49 19.19 0.08
21/22 11.52 15.57 0.04
22/23 11.21 30.36 0.07
23/24 12.23 10.31 0.09

Rock Island Dam

Correlation between spill and flow for each year, for Rock Island Dam
Run Year Mean Flow Mean Spill R-squared
05/06 110.06 9.17 0.61
06/07 117.21 8.11 0.48
07/08 102.50 8.01 0.59
08/09 103.16 7.92 0.66
09/10 85.63 5.91 0.50
10/11 120.70 11.34 0.60
11/12 139.25 18.61 0.84
12/13 140.42 16.55 0.78
13/14 118.38 15.52 0.49
14/15 121.38 13.09 0.00
15/16 106.98 7.67 0.38
16/17 131.33 20.11 0.80
17/18 131.02 24.07 0.82
18/19 101.78 8.49 0.69
19/20 99.23 9.74 0.54
20/21 113.29 14.76 0.69
21/22 112.32 9.05 0.19
22/23 118.21 20.68 0.82
23/24 86.04 5.97 0.26
Correlation between spill and temperature for each year, for Rock Island Dam
Run Year Mean Temperature Mean Spill R-squared
05/06 10.55 9.17 0.10
06/07 10.66 8.11 0.16
07/08 10.29 8.01 0.26
08/09 10.10 7.92 0.13
09/10 10.75 5.91 0.20
10/11 10.32 11.34 0.03
11/12 10.14 18.61 0.08
12/13 10.77 16.55 0.12
13/14 10.88 15.52 0.00
14/15 11.68 13.09 0.50
15/16 11.98 7.67 0.08
16/17 11.04 20.11 0.00
17/18 11.25 24.07 0.00
18/19 11.19 8.49 0.11
19/20 11.21 9.74 0.05
20/21 11.11 14.76 0.09
21/22 11.14 9.05 0.16
22/23 10.83 20.68 0.05
23/24 11.86 5.97 0.12

Rocky Reach Dam

Correlation between spill and flow for each year, for Rocky Reach Dam
Run Year Mean Flow Mean Spill R-squared
05/06 108.94 5.45 0.50
06/07 114.19 5.14 0.48
07/08 100.63 3.82 0.55
08/09 100.67 4.99 0.62
09/10 83.22 2.01 0.23
10/11 116.85 7.73 0.56
11/12 136.80 18.67 0.81
12/13 136.59 18.44 0.73
13/14 114.24 6.61 0.63
14/15 114.86 5.14 0.50
15/16 100.19 3.48 0.41
16/17 128.59 19.61 0.85
17/18 126.77 18.67 0.78
18/19 96.54 5.45 0.62
19/20 93.93 6.19 0.65
20/21 107.89 10.09 0.63
21/22 106.24 3.11 0.11
22/23 114.82 11.20 0.71
23/24 84.06 1.58 0.12
Correlation between spill and temperature for each year, for Rocky Reach Dam
Run Year Mean Temperature Mean Spill R-squared
05/06 10.54 5.45 0.04
06/07 10.64 5.14 0.04
07/08 10.28 3.82 0.12
08/09 10.09 4.99 0.10
09/10 10.74 2.01 0.24
10/11 10.31 7.73 0.02
11/12 10.13 18.67 0.03
12/13 10.75 18.44 0.09
13/14 10.87 6.61 0.10
14/15 11.67 5.14 0.04
15/16 11.96 3.48 0.03
16/17 11.03 19.61 0.03
17/18 11.23 18.67 0.00
18/19 11.18 5.45 0.04
19/20 11.20 6.19 0.00
20/21 11.10 10.09 0.08
21/22 11.13 3.11 0.22
22/23 10.82 11.20 0.03
23/24 11.85 1.58 0.15

Wells Dam

Correlation between spill and flow for each year, for Wells Dam
Run Year Mean Flow Mean Spill R-squared
05/06 109.27 6.93 0.55
06/07 113.57 9.49 0.62
07/08 101.25 4.60 0.56
08/09 101.33 6.90 0.67
09/10 83.73 2.86 0.52
10/11 116.28 8.77 0.59
11/12 135.89 21.32 0.82
12/13 136.07 17.36 0.75
13/14 114.37 7.12 0.70
14/15 116.89 4.86 0.43
15/16 101.79 4.63 0.60
16/17 127.72 12.14 0.76
17/18 125.75 17.40 0.79
18/19 97.89 6.87 0.66
19/20 95.25 5.36 0.56
20/21 109.59 10.14 0.69
21/22 105.17 6.65 0.32
22/23 114.67 14.26 0.80
23/24 82.86 2.68 0.23
Correlation between spill and temperature for each year, for Wells Dam
Run Year Mean Temperature Mean Spill R-squared
05/06 10.36 6.93 0.01
06/07 10.46 9.49 0.02
07/08 10.10 4.60 0.05
08/09 9.90 6.90 0.06
09/10 10.56 2.86 0.18
10/11 10.13 8.77 0.00
11/12 9.94 21.32 0.03
12/13 10.57 17.36 0.09
13/14 10.68 7.12 0.02
14/15 11.49 4.86 0.04
15/16 11.78 4.63 0.02
16/17 10.85 12.14 0.01
17/18 11.05 17.40 0.00
18/19 11.00 6.87 0.07
19/20 11.01 5.36 0.02
20/21 10.91 10.14 0.07
21/22 10.94 6.65 0.02
22/23 10.64 14.26 0.03
23/24 11.66 2.68 0.04

Ice Harbor Dam

Correlation between spill and flow for each year, for Ice Harbor Dam
Run Year Mean Flow Mean Spill R-squared
05/06 50.14 16.50 0.76
06/07 40.76 13.98 0.65
07/08 36.80 13.54 0.83
08/09 52.24 20.56 0.83
09/10 38.52 14.49 0.76
10/11 59.71 22.48 0.82
11/12 65.12 27.35 0.89
12/13 40.98 16.08 0.77
13/14 42.29 15.22 0.69
14/15 41.15 13.89 0.50
15/16 39.07 12.97 0.68
16/17 59.80 29.43 0.95
17/18 60.97 27.93 0.84
18/19 48.72 23.44 0.93
19/20 42.16 16.00 0.93
20/21 40.35 14.71 0.88
21/22 33.88 12.65 0.84
22/23 46.97 21.91 0.93
23/24 40.87 16.60 0.86
Correlation between spill and temperature for each year, for Ice Harbor Dam
Run Year Mean Temperature Mean Spill R-squared
05/06 11.90 16.50 0.01
06/07 12.00 13.98 0.06
07/08 11.64 13.54 0.01
08/09 11.44 20.56 0.04
09/10 12.10 14.49 0.12
10/11 11.67 22.48 0.00
11/12 11.49 27.35 0.03
12/13 12.11 16.08 0.04
13/14 12.23 15.22 0.00
14/15 13.03 13.89 0.06
15/16 13.32 12.97 0.01
16/17 12.39 29.43 0.06
17/18 12.59 27.93 0.00
18/19 12.54 23.44 0.00
19/20 12.56 16.00 0.00
20/21 12.46 14.71 0.01
21/22 12.49 12.65 0.00
22/23 12.18 21.91 0.00
23/24 13.20 16.60 0.00

Lower Granite Dam

Correlation between spill and flow for each year, for Lower Granite Dam
Run Year Mean Flow Mean Spill R-squared
05/06 49.31 12.10 0.73
06/07 40.13 8.91 0.59
07/08 36.57 9.87 0.85
08/09 51.32 12.31 0.81
09/10 38.75 8.67 0.70
10/11 58.88 14.32 0.79
11/12 64.01 15.30 0.82
12/13 40.20 9.08 0.66
13/14 41.63 8.78 0.55
14/15 40.86 7.98 0.39
15/16 39.24 6.92 0.49
16/17 58.95 19.21 0.87
17/18 59.50 14.83 0.71
18/19 47.94 12.87 0.81
19/20 41.78 13.87 0.80
20/21 39.78 13.45 0.82
21/22 33.49 10.96 0.77
22/23 46.82 16.43 0.86
23/24 40.60 17.13 0.85
Correlation between spill and temperature for each year, for Lower Granite Dam
Run Year Mean Temperature Mean Spill R-squared
05/06 11.01 12.10 0.02
06/07 11.11 8.91 0.12
07/08 10.75 9.87 0.03
08/09 10.55 12.31 0.06
09/10 11.21 8.67 0.14
10/11 10.78 14.32 0.01
11/12 10.59 15.30 0.05
12/13 11.22 9.08 0.08
13/14 11.33 8.78 0.05
14/15 12.13 7.98 0.11
15/16 12.43 6.92 0.09
16/17 11.50 19.21 0.03
17/18 11.70 14.83 0.03
18/19 11.65 12.87 0.01
19/20 11.66 13.87 0.02
20/21 11.56 13.45 0.02
21/22 11.59 10.96 0.00
22/23 11.29 16.43 0.00
23/24 12.31 17.13 0.00

7 Final fates, under median conditions

The figures below show the predicted final fates of fish from different natal tributaries under the median conditions in our study system from 2005-2024. The final fates for hatchery and natural origin fish are shown on each plot. However, in the case of the six Snake River tribuatries (Tucannon River, Clearwater River, Asotin Creek, Grande Ronde River, Salmon River, and Imnaha River), the difference between in-river and transported juvenile migrants is highlighted instead of the differences between rearing type, with a separate plot provided for each rearing type.

Fifteenmile Creek

Fifteenmile Creek, estimated final fates under median conditions from 2005-2024.
Fifteenmile Creek, estimated final fates under median conditions from 2005-2024.

Deschutes River

Deschutes River, estimated final fates under median conditions from 2005-2024.
Deschutes River, estimated final fates under median conditions from 2005-2024.

John Day River

John Day River, estimated final fates under median conditions from 2005-2024.
John Day River, estimated final fates under median conditions from 2005-2024.

Umatilla River

Umatilla River, estimated final fates under median conditions from 2005-2024.
Umatilla River, estimated final fates under median conditions from 2005-2024.

Walla Walla River

Walla Walla River, estimated final fates under median conditions from 2005-2024.
Walla Walla River, estimated final fates under median conditions from 2005-2024.

Yakima River

Yakima River, estimated final fates under median conditions from 2005-2024.
Yakima River, estimated final fates under median conditions from 2005-2024.

Wenatchee River

Wenatchee River, estimated final fates under median conditions from 2005-2024.
Wenatchee River, estimated final fates under median conditions from 2005-2024.

Entiat River

Entiat River, estimated final fates under median conditions from 2005-2024.
Entiat River, estimated final fates under median conditions from 2005-2024.

Methow River

Methow River, estimated final fates under median conditions from 2005-2024.
Methow River, estimated final fates under median conditions from 2005-2024.

Okanogan River

Okanogan River, estimated final fates under median conditions from 2005-2024.
Okanogan River, estimated final fates under median conditions from 2005-2024.

Tucannon River

Tucannon River natural origin, estimated final fates under median conditions from 2005-2024.
Tucannon River natural origin, estimated final fates under median conditions from 2005-2024.
Tucannon River hatchery, estimated final fates under median conditions from 2005-2024.
Tucannon River hatchery, estimated final fates under median conditions from 2005-2024.

Clearwater River

NOTE: Detection efficiency could not be estimated for the Clearwater River, because of the lack of a site close to the confluence with the Snake River. Therefore, the estimate of final fate in the Clearwater River is biased low, while the estimate of final fate in the mainstem state that connects to the Clearwater river (mainstem, upstream of LGR) is biased high.


Clearwater River natural origin, estimated final fates under median conditions from 2005-2024.
Clearwater River natural origin, estimated final fates under median conditions from 2005-2024.
Clearwater River hatchery, estimated final fates under median conditions from 2005-2024.
Clearwater River hatchery, estimated final fates under median conditions from 2005-2024.

Asotin Creek

Asotin Creek natural origin, estimated final fates under median conditions from 2005-2024.
Asotin Creek natural origin, estimated final fates under median conditions from 2005-2024.

Grande Ronde River

NOTE: Detection efficiency could not be estimated for the Clearwater River, because of the lack of a site close to the confluence with the Snake River. Therefore, the estimate of final fate in the Clearwater River is biased low, while the estimate of final fate in the mainstem state that connects to the Clearwater river (mainstem, upstream of LGR) is biased high.


Grande Ronde natural origin, estimated final fates under median conditions from 2005-2024.
Grande Ronde natural origin, estimated final fates under median conditions from 2005-2024.
Grande Ronde hatchery, estimated final fates under median conditions from 2005-2024.
Grande Ronde hatchery, estimated final fates under median conditions from 2005-2024.

Salmon River

NOTE: Detection efficiency could not be estimated for the Clearwater River, because of the lack of a site close to the confluence with the Snake River. Therefore, the estimate of final fate in the Clearwater River is biased low, while the estimate of final fate in the mainstem state that connects to the Clearwater river (mainstem, upstream of LGR) is biased high.


Salmon River natural origin, estimated final fates under median conditions from 2005-2024.
Salmon River natural origin, estimated final fates under median conditions from 2005-2024.
Salmon River hatchery, estimated final fates under median conditions from 2005-2024.
Salmon River hatchery, estimated final fates under median conditions from 2005-2024.

Imnaha River

Imnaha River natural origin, estimated final fates under median conditions from 2005-2024.
Imnaha River natural origin, estimated final fates under median conditions from 2005-2024.

Imnaha River hatchery, estimated final fates under median conditions from 2005-2024. Imnaha River, non-transported fish, estimated final fates under median conditions from 2005-2024.

Imnaha River, transported fish, estimated final fates under median conditions from 2005-2024.
Imnaha River, transported fish, estimated final fates under median conditions from 2005-2024.
Imnaha River, natural origin fish, estimated final fates under median conditions from 2005-2024.
Imnaha River, natural origin fish, estimated final fates under median conditions from 2005-2024.
Imnaha River, hatchery origin fish, estimated final fates under median conditions from 2005-2024.
Imnaha River, hatchery origin fish, estimated final fates under median conditions from 2005-2024.

8 Overshoot probabilities and homing

Probability (with 95% credible interval) of overshooting one or two or more dams by population. The Entiat River and Tucannon River populations are only able to overshoot one dam in our model (Wells Dam and Lower Granite Dam, respectively).
Population 1 2+
John Day River, Natural 0.32 (0.23 - 0.4) 0.11 (0.07 - 0.16)
Umatilla River, Natural 0.26 (0.18 - 0.35) 0.1 (0.06 - 0.15)
Umatilla River, Hatchery 0.25 (0.14 - 0.35) 0.06 (0.02 - 0.11)
Walla Walla River, Natural 0.26 (0.2 - 0.32) 0.16 (0.11 - 0.22)
Walla Walla River, Hatchery 0.35 (0.28 - 0.41) 0.27 (0.21 - 0.34)
Yakima River, Natural 0.1 (0.06 - 0.15) 0.05 (0.02 - 0.08)
Wenatchee River, Natural 0.03 (0 - 0.07) 0.02 (0 - 0.05)
Wenatchee River, Hatchery 0.05 (0.03 - 0.09) 0.16 (0.09 - 0.25)
Entiat River, Natural 0.36 (0.28 - 0.47)
Tucannon River, Natural (not transported) 0.53 (0.45 - 0.61)
Tucannon River, Natural (transported) 0.42 (0.03 - 0.71)
Tucannon River, Hatchery (not transported) 0.51 (0.44 - 0.58)
Tucannon River, Hatchery (transported) 0.24 (0.07 - 0.34)
Probability (with 95% credible interval) of homing, conditional on ascending the dam directly downstream of the natal tributary but not overshooting (No overshoot), overshooting one dam (1), or overshooting two or more dams (2+) by population. The Entiat River and Tucannon River populations are only able to overshoot one dam in our model (Wells Dam and Lower Granite Dam, respectively).
Population No overshoot 1 2+
John Day River, Natural 0.66 (0.55 - 0.75) 0.5 (0.42 - 0.57) 0.15 (0.07 - 0.25)
Umatilla River, Natural 0.68 (0.56 - 0.78) 0.67 (0.58 - 0.75) 0.26 (0.13 - 0.39)
Umatilla River, Hatchery 0.34 (0.2 - 0.51) 0.3 (0.2 - 0.42) 0.12 (0.04 - 0.25)
Walla Walla River, Natural 0.79 (0.62 - 0.89) 0.55 (0.44 - 0.65) 0.15 (0.1 - 0.23)
Walla Walla River, Hatchery 0.71 (0.6 - 0.84) 0.15 (0.1 - 0.35) 0.05 (0.02 - 0.11)
Yakima River, Natural 0.99 (0.93 - 1) 0.87 (0.75 - 0.95) 0.3 (0.12 - 0.55)
Wenatchee River, Natural 0.98 (0.93 - 1) 0.91 (0.67 - 1) 0.57 (0.17 - 1)
Wenatchee River, Hatchery 0.95 (0.89 - 0.98) 0.47 (0.33 - 0.63) 0.05 (0.02 - 0.1)
Entiat River, Natural 0.95 (0.89 - 0.99) 0.71 (0.6 - 0.82)
Tucannon River, Natural (not transported) 0.74 (0.6 - 0.86) 0.29 (0.21 - 0.37)
Tucannon River, Natural (transported) 0.69 (0.03 - 1) 0.14 (0.01 - 0.41)
Tucannon River, Hatchery (not transported) 0.6 (0.46 - 0.74) 0.28 (0.22 - 0.34)
Tucannon River, Hatchery (transported) 0.66 (0.29 - 0.9) 0.25 (0.14 - 0.37)

9 Deschutes River movement

Probability of movement into the Deschutes River by temperature, conditional on being in the reach of the mainstem Columbia between Bonneville and McNary Dam. Histograms on the plot margins indicate the temperature experiences of individual fish. Because this movement occurs within the Middle Columbia DPS, those populations have separate probabilities of movement, and are shown in panels A-F, while fish from the Upper Columbia DPS and the Snake River DPS have shared movement probabilities for this movement and are shown in panels G and H. Please note that in panel H, “not transported” refers to in-river juvenile migrants.
Probability of movement into the Deschutes River by temperature, conditional on being in the reach of the mainstem Columbia between Bonneville and McNary Dam. Histograms on the plot margins indicate the temperature experiences of individual fish. Because this movement occurs within the Middle Columbia DPS, those populations have separate probabilities of movement, and are shown in panels A-F, while fish from the Upper Columbia DPS and the Snake River DPS have shared movement probabilities for this movement and are shown in panels G and H. Please note that in panel H, “not transported” refers to in-river juvenile migrants.

10 Post-overshoot fallback by dam

The effect of winter spill days on post-overshoot fallback at each of the seven overshoot dams in this study. For each dam, populations are only visualized if there were at least 10 fish that both overshot the dam may have been affected by winter spill, based on their movement timing.
The effect of winter spill days on post-overshoot fallback at each of the seven overshoot dams in this study. For each dam, populations are only visualized if there were at least 10 fish that both overshot the dam may have been affected by winter spill, based on their movement timing.

11 En-route fallback as a function of spill volume

Bonneville Dam

Probability of fallback at Bonneville Dam, by volume of spill. Because this movement occurs within the Middle Columbia DPS, those populations have separate probabilities of movement, and are shown in panels A-H, while fish from the Upper Columbia DPS and the Snake River DPS have shared movement probabilities for this movement and are shown in panels I-L. Histograms on the plot margins indicate the spill experiences of individual fish.
Probability of fallback at Bonneville Dam, by volume of spill. Because this movement occurs within the Middle Columbia DPS, those populations have separate probabilities of movement, and are shown in panels A-H, while fish from the Upper Columbia DPS and the Snake River DPS have shared movement probabilities for this movement and are shown in panels I-L. Histograms on the plot margins indicate the spill experiences of individual fish.

McNary Dam

Probability of fallback at McNary Dam, by volume of spill. Because this movement at the juncture between the Middle Columbia, Upper Columbia, and Snake River DPS boundaries, every population has a unique probability of movement. All populations that are downstream of McNary Dam (the Fifteenmile Creek, Deschutes River, John Day River, and Umatilla River) are not shown because they are affected by winter spill days rather than spill volume for this movement, as it is a post-overshoot fallback movement. Histograms on the plot margins indicate the spill experiences of individual fish.
Probability of fallback at McNary Dam, by volume of spill. Because this movement at the juncture between the Middle Columbia, Upper Columbia, and Snake River DPS boundaries, every population has a unique probability of movement. All populations that are downstream of McNary Dam (the Fifteenmile Creek, Deschutes River, John Day River, and Umatilla River) are not shown because they are affected by winter spill days rather than spill volume for this movement, as it is a post-overshoot fallback movement. Histograms on the plot margins indicate the spill experiences of individual fish.

Ice Harbor Dam

Probability of fallback at Ice Harbor Dam, by volume of spill. Only Snake River populations are shown because an ascent of Ice Harbor Dam by any populations from the Middle or Upper Columbia would be overshoot and therefore the probability of fallback is affected by winter spill days rather than spill volume. Histograms on the plot margins indicate the spill experiences of individual fish.
Probability of fallback at Ice Harbor Dam, by volume of spill. Only Snake River populations are shown because an ascent of Ice Harbor Dam by any populations from the Middle or Upper Columbia would be overshoot and therefore the probability of fallback is affected by winter spill days rather than spill volume. Histograms on the plot margins indicate the spill experiences of individual fish.

Lower Granite Dam

Probability of fallback at Lower Granite Dam, by volume of spill. Only Snake River populations are shown because an ascent of Lower Granite Dam by any populations from the Middle or Upper Columbia would be overshoot and therefore the probability of fallback is affected by winter spill days rather than spill volume. The Tucannon River is also not shown because Lower Granite Dam is an overshoot for that population. Histograms on the plot margins indicate the spill experiences of individual fish.
Probability of fallback at Lower Granite Dam, by volume of spill. Only Snake River populations are shown because an ascent of Lower Granite Dam by any populations from the Middle or Upper Columbia would be overshoot and therefore the probability of fallback is affected by winter spill days rather than spill volume. The Tucannon River is also not shown because Lower Granite Dam is an overshoot for that population. Histograms on the plot margins indicate the spill experiences of individual fish.

12 Post-overshoot fallback as a function of March spill

This section presents shows Figures 5 and 6 from the main manuscript where the model is re-run where only days of spill in March are used as a covariate instead of days of spill in January, February, and March (as is used in the base model).

The effect of March spill days on movement probabilities out of the mainstem state directly upstream of the mainstem state that connects to the natal tributary for (A) John Day River natural origin Steelhead, (B) Umatilla River natural origin Steelhead, (C) Umatilla River hatchery origin Steelhead, (D) Yakima River natural origin Steelhead, (E) Walla Walla River natural origin Steelhead, (F) Walla Walla River hatchery origin Steelhead, (G) Wenatchee River natural origin Steelhead, (H) Wenatchee River hatchery origin Steelhead, (I) Entiat River natural origin Steelhead, (J) Tucannon River natural origin transported Steelhead, (K) Tucannon River natural origin in-river Steelhead, (L) Tucannon River hatchery origin transported Steelhead, and (M) Tucannon River hatchery origin in-river Steelhead. Histograms on the plot margins indicate the temperature experiences of individual fish.
The effect of March spill days on movement probabilities out of the mainstem state directly upstream of the mainstem state that connects to the natal tributary for (A) John Day River natural origin Steelhead, (B) Umatilla River natural origin Steelhead, (C) Umatilla River hatchery origin Steelhead, (D) Yakima River natural origin Steelhead, (E) Walla Walla River natural origin Steelhead, (F) Walla Walla River hatchery origin Steelhead, (G) Wenatchee River natural origin Steelhead, (H) Wenatchee River hatchery origin Steelhead, (I) Entiat River natural origin Steelhead, (J) Tucannon River natural origin transported Steelhead, (K) Tucannon River natural origin in-river Steelhead, (L) Tucannon River hatchery origin transported Steelhead, and (M) Tucannon River hatchery origin in-river Steelhead. Histograms on the plot margins indicate the temperature experiences of individual fish.


The homing probability for (A) John Day River, (B) Umatilla River, (C) Walla Walla River, (D) Wenatchee River, (E) Tucannon River transported, (F) Tucannon River in-river, (G) Entiat River, and (H) Yakima River Steelhead under different scenarios for basin-wide temperature and March spill days (0, 10, 20, or 30 days) at the overshoot dam. The temperature scenarios are specific run years from the dataset, with the coldest year being the 2011/2012 run year, the average year being the 2005/2006 run year, and the warmest year being the 2015/2016 run year.
The homing probability for (A) John Day River, (B) Umatilla River, (C) Walla Walla River, (D) Wenatchee River, (E) Tucannon River transported, (F) Tucannon River in-river, (G) Entiat River, and (H) Yakima River Steelhead under different scenarios for basin-wide temperature and March spill days (0, 10, 20, or 30 days) at the overshoot dam. The temperature scenarios are specific run years from the dataset, with the coldest year being the 2011/2012 run year, the average year being the 2005/2006 run year, and the warmest year being the 2015/2016 run year.

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